光诱导为安全视觉的安全视觉
Juhyung Seo1, Seungme Kang1, Chaehyun Kim2
1Department of Electronic Engineering, Hanyang University, Seoul, Republic of Korea.
Advanced materials (Deerfield Beach, Fla.)
|January 29, 2026
概括
一个新的基于光的真随机数发生器 (PS-TRNG) 使用光物质相互作用来创建高随机数. 这项技术可以实现安全的图像身份验证,甚至可以检测人工智能生成的操作.
科学领域:
- 材料科学 材料科学 材料科学
- 光电学是指光电子产品.
- 信息安全 信息安全
背景情况:
- 真正随机数生成器 (TRNG) 对于安全的数据加密和身份验证至关重要.
- 现有的TRNG通常面临,统计质量或长期稳定性方面的局限性.
- 开发新奇的物理现象,用于强大的随机数生成是一个正在进行的研究领域.
研究的目的:
- 开发一个基于光的真随机数发生器 (PS-TRNG),利用光物质相互作用和电荷捕获.
- 为了研究铜酸盐 (CuV2O6) 纳米结构和二氧化 (SnO2) 量子点用于随机数生成的潜力.
- 在移动系统中实现PS-TRNG用于图像真实性验证.
主要方法:
- 将CuV2O6纳米结构与SnO2量子点层集成,以创建一个PS-TRNG设备.
- 在光脉冲列车下利用概率的捕捉-解捕获动态来产生随机的光峰电流.
- 开发一个带有定制电路板的移动平台,用于嵌入随机数字到图像数据中.
- 使用NIST统计测试套件测试随机数输出,并评估图像修改检测能力.
主要成果:
- PS-TRNG 显示出高度,并使多级 (二次) 随机数生成成为可能.
- 输出实现了接近理想的统计性质 (33.30%的统一性,33.28%的哈明间距离),并通过了所有15个NIST测试.
- 集成系统成功验证了图像的真实性,检测了复杂的AI生成的修改.
- 该设备表现出卓越的长期稳定性,运行超过200万个周期,可靠性超过460天.
结论:
- 基于Photospike的真随机数生成器提供了一个强大的,稳定的高质量的随机数源.
- 基于硬件的图像真实性验证中,PS-TRNG技术是有效的,即使对先进的AI操纵也有效.
- 这种方法为安全的数据生成和数字内容保护提供了有希望的解决方案.
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